Research Papers: Gas Turbines: Turbomachinery

Multidisciplinary Design and Optimizations of Swept and Leaned Transonic Rotor

[+] Author and Article Information
Seyed Reza Razavi

Quality System Engineering Department,
Concordia University,
1455 De Maisonneuve Boulevard West,
Montreal, QC H3G 1M8, Canada
e-mail: s_raz@encs.concordia.ca

Shervin Sammak

Center for Research Computing,
University of Pittsburgh,
3700 Ohara Street,
Pittsburgh, PA 15261
e-mail: shervin.sammak@pitt.edu

Masoud Boroomand

Department of Aerospace Engineering,
Tehran Polytechnic,
424 Hafez Avenue,
Tehran 15875-4413, Iran
e-mail: boromand@aut.ac.ir

1Corresponding author.

Contributed by the Turbomachinery Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received April 30, 2017; final manuscript received May 30, 2017; published online August 23, 2017. Editor: David Wisler.

J. Eng. Gas Turbines Power 139(12), 122601 (Aug 23, 2017) (11 pages) Paper No: GTP-17-1155; doi: 10.1115/1.4037456 History: Received April 30, 2017; Revised May 30, 2017

Optimization problems in many engineering applications are usually considered as complex subjects. Researchers are often obliged to solve a multi-objective optimization problem. Several methodologies such as genetic algorithm (GA) and artificial neural network (ANN) are proposed to optimize multi-objective optimization problems. In the present study, various levels of sweep and lean were exerted to blades of an existing transonic rotor, the well-known NASA rotor-67. Afterward, an ANN optimization method was used to find the most appropriate settings to achieve the maximum stage pressure ratio, efficiency, and operating range. At first, the study of the impact of sweep and lean on aerodynamic and performance parameters of the transonic axial flow compressor rotors was undertaken using a systematic step-by-step procedure. This was done by employing a three-dimensional (3D) compressible turbulent model. The results were then used as the input data to the optimization computer code. It was found that the optimized sweep angles can increase the safe operating range up to 30% and simultaneously increase the pressure ratio and subsequently the efficiency by 1% and 2%. Moreover, it was found that the optimized leaned blades, according to their target function, had positive (forward (FW)) or negative (backward (BW)) optimized angles. Leaning the blade at the optimum point can increase the safe operating range up to 12% and simultaneously increase the pressure ratio and subsequently the efficiency by 4% and 5%.

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Fig. 1

Meridional view of rotor-67 showing the locations of available experimental data

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Fig. 2

Positive and negative leaned and swept blades [19]

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Fig. 3

Sigmoid function output according to neuron input

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Fig. 5

Learning coefficient according to training loop number

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Fig. 7

Training error against iteration: (a) swept blade and (b) leaned blade

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Fig. 8

Schematic of boundary condition

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Fig. 9

2D grid between blades at midspan

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Fig. 10

3D H, J, C, and L grid

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Fig. 11

Map of the rotor for the three grid types: (a) efficiency and (b) pressure ratio against mass flow rate

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Fig. 12

Relative Mach number at 90% of span and near stall: (a) Experimental and (b) computations

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Fig. 13

Relative Mach number at 30% of span and near peak efficiency: (a) Experimental and (b) computations

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Fig. 14

Backward leaned blade implementation on section number two

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Fig. 15

Comparison of curved rotor: (a) swept blade (negative sweep) and (b) leaned blade (positive lean)

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Fig. 16

Impact of FW-sweep at different sections against an unswept blade: (a) Pr against normalized mass flow rate and (b) Eff against normalized mass flow rate

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Fig. 17

Impact of BW-sweep at midsections on an unswept blade: (a) efficiency against mass flow rate and (b) pressure ratio against normalized mass flow rate

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Fig. 18

Impact of FW-lean at midsections on unswept blade

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Fig. 19

Impact of BW-lean at midsections on unswept blade

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Fig. 20

Flow direction before and after shock around an unsweep rotor

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Fig. 21

Impact of FW-sweep on shock structure: (a) forward rotor and (b) basic blade

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Fig. 22

Optimized rotor (swept rotor with target function of all parameters) profile as compared to basic rotor: (a) optimized rotor and (b) basic rotor

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Fig. 23

Three parameter optimized rotor's operating line



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